Ann. Agric. Res. New×Series Vol. 38 (2) interactions : 235-241 (2017) Genotype environment and stability analysis for root yield and quality traits
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Genotype x environment interactions and stability analysis for root yield and quality traits in sugarbeet (Beta vulgaris L.) Gulzar S. Sanghera1*, K.S. Thind2, Navdeep Singh3, Rupinder Pal Singh4 and V. Tyagi5 Regional Research Station, Punjab Agricultural University, Kapurthala-144601, Punjab e-mail:
[email protected] Received : February 2017 ; Revised Accepted: May 2017
ABSTRACT Five sugarbeet genotypes were tested across nine environments (three dates of sowing; three locations) during Rabi 2014-15 to assess the magnitude of genotype × environment interactions and stability for root yield and quality traits in sugarbeet. Pooled analysis of variance showed highly significant G × E interactions for characters like root length, root fresh weight, leaf fresh weight, whole plant weight, sucrose percentage and brix percentage. The environment and genotype × environment (E + G × E) component was highly significant for root length, root fresh weight, root dry weight, whole plant weight, root yield and sugar yield. Stability parameters viz., mean performance over environments (µ), the linear regession (bi) and deviation from regression (S2di ) were measured for root yield and quality parameters which revealed that Magnolia and Cauvery genotypes exhibited higher root yield (80.7 and 78.8 t/ha) and below average stability (bi < 1.0). Calixta genotype recorded highest sucrose (15.3 %) and regression coefficient more than unity (bi > 1.0) coupled with significant regresson deviation. Magnolia and Cauvery exhibited higher sugar yield than mean yield and below average stability, but their performance was unpredictable. Genotypes that showed stability but were poor in mean performance can be involved in crosses with agronomically desirable genotypes for respective characters, in a compensating manner in order to give constant performance of the trait. Key words: G × E interactions, root yield, sucrose, stability parameters.
Sugarbeet (Beta vulgaris L.) is a member of Chenopodiaceae family, whose roots contain a high concentration of sucrose. It is commercially grown for sugar production, especially in temperate countries. The production of sugarbeet in the world during 2014 was about 266.8 million tons with acreage of 4.47 million ha with an *Correspondence address :
[email protected] 1,5 PAU Regional Research Station, Kapurthala-144601, Punjab, India. 2 Head, Department of Plant Breeding, PAU, Ludhiana, 141004, Punjab, India. E-mail :
[email protected] 3 Department of Plant Breeding, PAU, Ludhiana. E-mail:
[email protected] 4 PAU Regional Research Station, Kapurthala, 144601, Punjab, India. E-mail: vikranttyagi97@gmail
average root yield of 59.6 t/ha (Anonymous, 2014). European Union, USA and Russia are the three largest sugarbeet producers in the world. In India, it is grown in a limited area. Nearly about 30% of sugar worldwide is produced from sugarbeet. Punjab state has favourable climatic conditions where sugarbeet can be successfully cultivated. Though, it is a short season Rabi crop (October-May), its yields are equivalent to that of sugarcane with 16-22 % sucrose content. The crop matures in April-May, when the canecrushing season is nearly over. Thus, supply of sugarbeet can extend the crushing season of sugar mills by nearly 2 months. Marlander (1991) demonstrated that the yield potential of sugarbeet depends primarily
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on site and year effects, whereas the influence of agronomic practices is much lower. The effect of the site can be attributed mainly to its constant characteristics of soil and climate and their interactions. Thus, the genotype × environment interaction (G × E) is very important for plant breeding, mainly concerning the development of improved and superior genotypes. Various studies have been done in evaluating the stability of various sugarbeet varieties in different areas by using methods of parametric univariate (Ebrahimian et al., 2008); regression analysis is certainly the most popular method for stability analysis. In addition to location or environment, time of sowing is also a very important variable for determination of appropriate growth period required for proper photosynthetic activity, growth and productivity. It is a known fact that cultivar yield depends upon different factors like variety, environment and management practices. Therefore, the present study was planned to estimate the genotype × environment interactions for root yield, its components and quality traits in sugar beet under Punjab conditions. MATERIALS
AND
METHODS
The field experiments were conducted over 9 environments comprising 3 locations viz., experimental field area of Department of Agronomy, Punjab Agricultural University, Ludhiana, Research Station, Faridkot and Regional Research Station, Kapurthala and three date of sowing (15 October, 30 October and 15 November) during Rabi 2014-15 to assess the genotype × environment interactions for root yield and quality traits in sugarbeet. The experimental plant materials for the study consisted of five sugarbeet genotypes namely Calixta, Magnolia, Cauvery, Shubra and Indus. All the sugarbeet genotypes were sown in randomized complete block design (RCBD) with three replications across nine environments having a plot size of 6 rows × 6 m length with inter-row and intra-row spacing of 75 cm and 15 cm, respectively. All the cultural and agronomic practices were followed to raise the crop. The data were recorded on five representative plants of each genotype (leaving the border rows) in each replication in all the nine environments for different traits root yield traits viz. germination (%)
recorded on plot basis, initiation of root swelling (days), number of leaves at maximum growth stage, number of leaves at root swelling stage, root diameter (cm), root length (cm), top fresh weight (kg), root fresh weight (kg), root dry weight (kg), whole plant weight (kg) and root yield (t/ha). Further, at maturity (180 DAS), five healthy roots were chosen at random from the ridges of each plot to determine quality characters using standard procedures. The quality parameter brix° (%) was determined polarimetrically on lead acetate extract of fresh macerated roots according to the method of Le-Docte (1927) and sucrose (%) and purity (%) from the juice were estimated using digital sucroanalyzer. Sugar yield (t/ha) was calculated by multiplying root yield (t/ha) by sucrose percentage. The mean values all the traits from each genotype in each replication were used for analysis of variance (Fisher, 1954) and estimation of stability parameters was done as per Eberhart and Russell model (1966). The analysis of the experimental design was based on the linear model with the help of software BMM. RESULTS
AND
DISCUSSION
Analysis of variance studies Analysis of variance for different characters studied in sugarbeet genotypes revealed highly significant differences among genotypes for root length, root fresh weight, root diameter, root dry weight, whole plant weight, juice purity, root yield and sugar yield. The G × E interactions were significant for different characters like; root diameter, root dry weight, sucrose percentage, brix° (%), juice purity, root yield and sugar yield (Table 1). Pooled analysis of variance was performed and showed highly significant G × E interactions for characters like root length, root fresh weight, leaf fresh weight, whole plant weight, sucrose percentage and brix° (%) (Table 2). It indicated that the phenotypic expression of all the genotypes, studied for different characters varied in different environments. The environment and genotype × environment (E + G × E) component was highly significant for number of leaves at maximum growth stage, number of leaves at initiation of root swelling, root length, root fresh
Genotype × environment interactions and stability analysis for root yield and quality traits
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Table 1. Analysis of variance (ANOVA) for different traits in sugarbeet. S. No.
Traits
Mean due to S.V.
Genotype (G)
Environments (E)
G× E
Pooled Error
4
8
32
72
8.92 19.80* 0.31 14.39 8.7* 71.39** 0.51** 1.00** 0.21 3.39* 472.76** 6.87** 4.47** 14.42** 11.98**
6.33 0.62 5.84* 7.7 11.81* 31.43** 1.06** 9.07** 1.54** 34.44** 813.81** 2.70* 7.62** 5.89 19.19**
11.28 4.32 1 6.75 6.2 21.43* 0.15** 0.35 0.1 1.39 557.36** 2.06** 2.62** 6.14* 12.98**
8.6 2.82 1.95 8.15 8.22 10.36 0.02 0.25 0.1 0.95 123.13 1.01 0.82 3.69 3.28
df 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Germination (%) Initiation of root swelling (DAS) No. of leaves at maximum growth (No.) No. of leaves at root swelling (No.) Root length (cm) Root diameter (cm) Top fresh weight (kg) Root fresh weight (kg) Root dry weight (kg) Whole plant weight (kg) Root yield (t/ha) Brix (%) Sucrose (%) Juice purity (%) Sugar yield (t/ha)
*Significant at P < 0.05 and **significant at P < 0.01
Table 2. Pooled analysis of variance for G × E interactions for different traits in sugarbeet Mean Sum of Squares S. No.
Trait
S.V. d.f.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Germination (%) Initiation of root swelling (DAS) No. of leaves at maximum growth (No.) No. of leaves at root swelling (No.) Root length (cm) Root diameter (cm) Top fresh weight (kg) Root fresh weight (kg) Root dry weight (kg) Whole plant weight (kg) Root yield (t/ha) Brix (%) Sucrose (%) Juice purity (%) Sugar yield (t/ha)
*Significant at P < 0.05 and **significant at P 1) indicated that it can perform better for this trait under favorable conditions.
Mean performance pooled over environments (Table 3) showed that genotype Calixta had maximum root yield (80.7 t/ha) and was statistically at par with other genotypes except Shubra. Shubra recorded significantly lower yield than Calixta (70.2 t/ha). The results also revealed that Magnolia and Cauvery exhibited higher root yield (80.7 t/ha and 78.8 t/ha) and below average stability (bi < 1.0). Thus, both of genotypes may be adapted to favourable environmental conditions, but their performance was unpredictable. Shubra and Indus with yield 70.2 t/ha and 73.5 t/ha, respectively and regression coefficient near unity (bi =0.90 and bi =0.60) but significant (S2di) indicated average stability and they may not exhibit the same level of performance over all environments. Sanbuichi et al. (1981) also evaluated several varieties at six sites and observed that Hokkai 41 showed the greatest stability for root yield, sugar content and sugar yield. Linear regression for the average root and sugar yield of a single genotype on the average yield of all genotypes in each environments resulted in regression coefficient (bi values) ranging from -0.06 to 1.93 and 0.19 to 1.71 for root and sugar yield, respectively. This large variation in regression coefficient explains different responses of genotypes to environmental changes (Akura et al., 2005). For quality traits (Table 3), Cauvery had high value of sucrose percent (15.3) and Magnolia had lowest (14.4). None of the five genotypes significantly different from each other for sucrose (%). All the sugarbeet genotypes studied exhibited significant deviation from regression (S2di) for sucrose percent in juice and thus the stablity as well as adaptability of these genotypes over environments were unpredictable. Although, Cauvery and shubra showed higher sucrose percent in juice and regression coefficient (b i =0.13 and b i =0.30), respectively. These genotypes may not exhibit the same levels of performance over all the environments as they had significant deviation from regression. Calixta genotype had highest sucrose (15.33%) and regression coefficient less than unity (bi > 1) coupled with significant regresson deviation so it could perfrom better under unfavourable environmental conditions. Table 4 depicts the
.
Germination (%) Initiation of root swelling (DAS) µ biSE Sdi2 µ biSE Sdi2 Calixta 85.85 1.07±0.78* 6.26** 34.89 0.60±1.20 1.44** Magnolia 85.67 0.40±0.38 1.50 35.15 0.19±0.83 0.69* Cauvery 86.37 1.10±0.48* 2.37* 36.19 0.058±1.10 1.21** Shubra 86.96 1.00±0.52* 2.77* 35.85 1.07±1.45 2.12** Indus 86.33 1.40±0.58* 3.49* 37.04 3.18±0.39** 0.15 Mean±SEM 85.84±0.54 35.82±0.99 LSD (0.05) 6.01 2.52 Genotypes Root length (cm) Root diameter (cm) µ biSE Sdi2 µ biSE Sdi2 Calixta 28.32 0.79±0.73 10.20** 11.21 0.35±0.52 13.76** Magnolia 27.52 0.69±0.49 4.70** 10.46 0.25±0.66 22.23** Cauvery 28.89 1.25±0.42* 3.39* 9.62 0.41±0.79 32.01** Shubra 28.04 1.52±0.57* 6.21** 10.41 0.53±0.66 21.93** Indus 27.57 0.85±0.61 7.26** 9.54 0.74±0.54 14.77** Mean±SEM 28.07±0.56 11.25±0.63 LSD (0.05) 4.65 0.71 Genotypes Top fresh weight (kg) Whole plant weight (kg) µ biSE Sdi2 µ biSE Sdi2 Calixta 0.96 0.92±0.16* 0.056 4.57 0.92±0.05* 0.25* Magnolia 1.12 1.17±0.093** 0.088 5.38 1.06±0.03** 0.1** Cauvery 1.16 1.17±0.15** 0.049 5.35 1.03±0.07** 0.53** Shubra 1.02 0.97±0.10* 0.023 4.67 0.97±0.05* 0.27* Indus 0.93 0.75±0.098 0.020 5.28 1.00±0.03** 0.01 Mean± SEM 1.04±0.12 5.06±0.04 LSD (0.05) 0.53 1.48 Genotypes Juice purity (%) Root yield (t/ha) µ biSE Sdi2 µ biSE Sdi2 Calixta 85.00 0.31±0.74 5.26** 80.74 0.92±0.22** 64.13** Magnolia 83.95 1.19±0.73 5.14** 78.87 1.08±0.22** 68.15** Cauvery 85.60 1.86±1.03 10.14** 75.73 1.48±0.36** 174.52** Shubra 85.34 1.15±1.25 14.90** 70.21 0.90±0.45 264.81** Indus 84.64 0.94±0.68 4.43** 73.58 0.60±0.39 200.57** Mean± SEM 85.04±0.88 75.82±0.32 LSD (0.05) 3.38 9.08 *Significant at P≤ 0.05 and **significant at P≤0.01
No. of leaves at maximum growth No. of leaves at root swelling µ biSE Sdi2 µ biSE Sdi2 17.60 0.77±0.35 2.98** 6.93 1.99±0.50** 0.12 17.22 0.71±0.25* 1.54 6.30 0.022±1.06 0.55* 18.48 1.23±0.22** 1.19 6.11 2.23±1.70 0.88** 17.81 1.14±0.27** 1.74 6.59 0.91±0.66 0.79** 18.52 1.13±0.29** 1.20 7.26 0.13±0.66 0.21 17.92±0.27 6.64±0.91 2.51 2.07 Root fresh weight (at harvest) (kg) Root dry weight (at harvest) (kg) µ biSE Sdi2 µ biSE Sdi2 2.05 1.03±0.017** 0.006** 0.93 1.26±0.15** 0.04** 1.87 1.03±0.041** 0.03** 0.86 1.09±0.13** 0.02** 2.15 1.15±0.054** 0.06** 0.80 0.93±0.23** 0.09** 1.72 0.95±0.06** 0.08** 0.65 0.92±0.23** 0.02** 1.85 0.96±0.11** 0.20** 0.61 0.78±0.053** 0.004** 1.75±0.05 0.77±0.15 0.77 0.23 Sucrose (%) Brix◦ (%) µ biSE Sdi2 µ biSE Sdi2 15.33 0.002±0.53 3.50** 18.08 0.22±0.51 3.16** 14.40 0.018±0.65 5.16** 17.32 0.029±0.64 5.02** 15.31 0.13±0.43 2.29* 18.03 0.32±0.46 2.60** 15.30 0.33±0.72 6.69** 17.89 0.43±0.68 5.69** 14.96 0.25±0.52 3.45* 18.04 0.044±0.54 3.60** 15.07±0.56 17.60±0.54 1.64 1.69 Sugar yield (t/ha) µ biSE Sdi2 12.05 1.02±0.19** 1.13 11.14 1.21±0.22** 1.53 11.34 1.46±0.44* 6.16** 10.43 0.83±0.37 4.34** 10.49 0.46±0.36 4.05** 11.09±0.31 1.97
Table 3. Means and phenotypic stability parameters for different characters in five sugarbeet genotypes
Genotypes Genotype × environment interactions and stability analysis for root yield and quality traits 239 239 239
Sanghera et al.
H+ H+ M+ L– L–
H+ H+ M– L– L–
stability characteristics of five sugar beet genotypes tested over nine environments.
Where, +, - denote the genotype had a regression coefficient significantly greater or less than one respectively, at P < 0.01. H denotes greater than average mean. L denotes lesser than average mean. M denotes average mean.
H– M– H– H– H– M– L– H– H– L– H– L– H– H– L– H– L– L– L– H– Calixta Magnolia Cauvery Shubra Indus
H– H– H– L– H–
L– L– H– M– H+
H+ L– L– M– H–
H+ H+ H+ M+ L+
L+ M+ H+ L+ H+
H– L– H– M– L–
H+ L+ H+ L+ L+
H+ H+ H+ L+ L+
Juice purity (%) Whole plant weight (kg) Root diameter (cm) Root length (cm) Root fresh weight (kg) Germina- Initiation No. of Top of root leaves at fresh tion (percent- swelling maximum weight age) (DAS) root swelling (kg) Character
Table 4. Stability characteristics of five sugar beet genotypes tested over nine environments.
Root dry weight (kg)
Sucrose (%)
Brix° %
Root yield (t/ha)
Sugar yield (t/ha)
240
Mean performance pooled over environments showed that genotype Calixta had maximum sugar yield (12.05 t/ha) and was statistically at par with other genotypes except Shubra and Indus. None of the five genotypes studied was found to be stable w.r.t. sugar yield as all of them had highly significant values for deviation from regression (S2di). Magnolia and Cauvery exhibited higher sugar yield than mean yield and below average stability (Table 3). Thus, both of genotypes may be adapted to favourable environmental conditions, but their performance was unpredictable. Stability analysis revealed that none of the genotypes involved in this investigation exerted stability for all the characters. Different genotypes had high phenotypic stability for different characters. From this study, it is suggested that linear regression could simply be regarded as measure of response of a particular genotype, whereas mean square of deviation from regression (S 2d i ) could be considered as a measure of stability. In this study, the mean performance (µ) and deviation from regression (S 2d i ) of each genotype were considered for stability and bi was used for testing the varietal response. Genotypes with lowest or nonsignificant S2di depicted stability in traits and vice-versa. The three parameters viz., µ, bi and S2di together provided an idea of adaptability of genotypes across the environments. Since, the individual variety means were regressed against the mean of all the genotypes, the population mean had a regression coefficient of 1.0. When the regression coefficient is unity (b i =1), it indicates average stability to change in environments. Genotypes with higher bi value (bi>1) indicate below average stability and higher sensibility to environmental changes. Such genotypes would perform better in high yielding or favourable environments but its performance will be lower in stress environments as compared to its genetic potential. Reverse is true when bi value unity (bi < 1). It means above average in stability and hence these genotypes perform better in unfavourable or stress environments.
Genotype × environment interactions and stability analysis for root yield and quality traits
The genotypes Calixta and Magnolia found stable for root yield and sugar yield may be used in future breeding programme by crossing between stable lines and selecting among their progenies. The populations involving high × high stability parents than those of high × low or low × low stability combinations result in high proportion of superior buffering segregates. Genotypes Cauvery and Shubra showed stability
241 241 for sucrose (%) and juice purity (%) were poor in 241
mean performance, hence could be involved in hybridization with agronomically superior genotypes to incorporate their linear stability. Since, the plant breeder is interested in yield; therefore evaluation of genotypes for stability should be primarily based on yield and yield contributing traits across locations.
REFERENCES Akura, M., Kaya, Y. and Taner, S., 2005. Genotype-environment interaction and phenotypic stability analysis for grain yield of durum wheat in the central Anatolian region. J Agric., 29: 369-375. Anonymous, 2014. Area and production of sugarbeet in world. http://faostat3.fao.org/ compare/E. Eberhart, S.A. and Russel, W.A., 1966. Stability parameters for comparing varieties. Crop Sci., 6: 36-40. Ebrahimian, H.R., Sadeghian, S.Y., Jahadakbar, M.R. and Abasi, Z., 2008. Study of adaptability and stability of sugarbeet monogerm cultivars in different locations of Iran. J. Sugar Beet, 24: 1-13. El-Hinnawy, H.H., Ahmed, E.A., Ramadan, B.S. H., Farag, M.A., Al-Jabawi, E.M., Mahmoud, M.R., Baron, P. and Bayoumi, M.R. 2002. Variety × environmental interaction in sugarbeet trials. Proc Int Conf on Arab Region and Africa in the world sugar context, 9-12
March, Aswan, Egypt. El-Sheikh, S.R.E.A., Enan, S.A., Maha, M. and ElZeni., 2008. Stability analysis of some sugarbeet varieties under different environment conditions. Egypt J. of Appl. Sci., 23(11): 10221. Fisher, R.A., 1954. A fuller theory of "junctions" in inbreeding. Heredity, 8: 187-197. Le-Docte, A., 1927. Commercial determination of sugar in the beet root using the sacks. Int. Sug. J., 29: 488-492. Marlander, B., 1991. Zuckerrüben.Optimierung von Anbauverfahren - Züchtungsfortschritt -Sortenwahl.uteBernhardt-Pätzold, Stadthagen, pp. 3-12. Sanbuichi, T., Matsuzaki, Y., Yoshida, T., Tsukishima, N., Kurosawa, K., Tudsumi, T., Mukalyama, K., Ara, K. and Sako, K., 1981. Varietal differences in response to cultivation and environmental conditions in sugar beet. Pl. Breed., 53: 5682-87.
